This Library provides a C++ interface querying, reading and writing Naif SPICE kernels. Built on the [Naif Toolkit](https://naif.jpl.nasa.gov/naif/toolkit.html).
This Library provides a C++ interface querying, reading and writing Naif SPICE kernels. Built on the [Naif Toolkit](https://naif.jpl.nasa.gov/naif/toolkit.html).
## Building The Library
The library leverages anaconda to maintain all of its dependencies. So in order to build SpiceQL, you'll need to have Anaconda installed.
## Getting Started
> **NOTE**:If you already have Anaconda installed, skip to step 3.
We reccomend installing using [miniforge](https://github.com/conda-forge/miniforge)
1. Download either the Anaconda or Miniconda installation script for your OS platform. Anaconda is a much larger distribtion of packages supporting scientific python, while Miniconda is a minimal installation and not as large: Anaconda installer, Miniconda installer
```
1. If you are running on some variant of Linux, open a terminal window in the directory where you downloaded the script, and run the following commands. In this example, we chose to do a full install of Anaconda, and our OS is Linux-based. Your file name may be different depending on your environment.
mamba install -c conda-forge spiceql
* If you are running Mac OS X, a pkg file (which looks similar to Anaconda3-5.3.0-MacOSX-x86_64.pkg) will be downloaded. Double-click on the file to start the installation process.
```
1. Open a Command line prompt and run the following commands:
To create the inital database, set your required environment variables.
```bash
```bash
# Clone the Github repo, note the recursive flag, this library depends on
# Path to some directory with kernels. SpiceQL searches for them recusively
# submodules that also need to be cloned. --recurse-submodules enables this and
# Create new environment from the provided dependency file, the -n flag is
# proceded by the name of the new environment, change this to whatever works for you
conda env create -f environment.yml -n ssdev
# activate the new env
conda activate ssdev
# make and cd into the build directory. This can be placed anywhere, but here, we make
# it in the repo (build is in .gitingore, so no issues there)
mkdir build
cd build
# Configure the project, install directory can be anything, here, it's the conda env
cmake .. -DCMAKE_INSTALL_PREFIX=$CONDA_PREFIX
# Optional: DB files are installed by default in $CONDA_PREFIX/etc/SpiceQL/db to
# use files that are included within the repo, you must create and define
# an environment variable named SSPICE_DEBUG.
# note SSPICE_DEBUG can be set to anything as long as it is defined
export SSPICE_DEBUG=True
# Set the environment variable(s) to point to your kernel install
# The following environment variables are used by default in order of priority:
# $SPICEROOT, $ALESPICEROOT, $ISISDATA.
# SPICEROOT is unique to this lib, while ALESPICEROOT, and ISISDATA are used
# by both ALE and ISIS respectively.
# note you can set each of these environment variables path to point to the
# correspoding kernels downloaded location, ie
SPICEROOT=~/spiceQL/Kernals/spiceRootKernel
ALESPICEROOT=~/spiceQL/Kernals/aleSpiceRootKernel
ISISDATA=~/spiceQL/Kernals/isisData
# build and install project
make install
# Optional, Run tests
ctest -j8
```
```
You can disable different components of the build by setting the CMAKE variables `SPICEQL_BUILD_DOCS`, `SPICEQL_BUILD_TESTS`, `SPICEQL_BUILD_BINDINGS`, or `SPICEQL_BUILD_LIB` to `OFF`. For example, the following cmake configuration command will not build the documentation or the tests:
Run `create_database()`, this is more easily done through python.
!!! warning
This might take serveral hours depending on the number of kernels in your folder
The SpiceQL API is available via Python bindings in the module `pyspiceql`. The bindings are built using SWIG and are on by default. You can disable the bindings in your build by setting `SPICEQL_BUILD_BINDINGS` to `OFF` when configuring your build.
Some functions allow for running over the web, these contain the optional parameter `useWeb`. See the [function list](SpiceQLCPPAPI/namespace_spice_q_l.md) for a list of functions with this parameter.
## Memoization Header Library
=== "Python"
```python
import pyspiceql as psql
# Make a query and it will return the kernels used
SpiceQL has a simple memoization header only library at `Spiceql/include/memo.h`. This can cache function results on disk using a binary archive format mapped using a combined hash of a function ID and its input parameters.
=== "C++"
TLDR
```C++
```C++
#include "memo.h"
#include <spiceql/spiceql.h>
#include <nlohmann/json.hpp>
// Make a query and it will return the kernels used
